Deputies Expenditure Analysis: My Questions

Introduction

The present work is a continuation of https://rpubs.com/manoelf/416750 Here we are going to create new questions and answer it through the data analysis. The data about deputies expenses is located right here https://canvas.instructure.com/courses/1402758/files/67618888/download?verifier=ibyou5PYo9aaFgRaefc0keYkHhkQ2EqIArdmI1bq&wrap=1 and more informations about you can find in http://www2.camara.leg.br/transparencia/acesso-a-informacao/copy_of_perguntas-frequentes/cota-para-o-exercicio-da-atividade-parlamentar

/TODO: Should talk here about the data, what does mean the variables and so on.

Set Up

For our analisys we need the folowing packages to be installed.

#install.packages("ggplot2")
#install.packages("dplyr")
#install.packages("tidyr")
#install.packages("scales")
#install.packages("plotly")

Once packages installed we load it.

library(ggplot2)
library(dplyr)
library(tidyr)
library(scales)
library(plotly)

Setting up the workspace.

Now we gonna load the main data, which is about the deputies expenses.

It is important to know how much money is expende along the months, for that reason we will se it through the graphic.

First we need to create two new column which represents the year of the expense and its month

expenses_by_month <- data %>%
  mutate(yar = substr(dataEmissao, 1, 4)) %>%
  mutate(month = substr(dataEmissao, 6, 7))

Error in data %>% mutate(yar = substr(dataEmissao, 1, 4)) %>% mutate(month = substr(dataEmissao,  : 
  não foi possível encontrar a função "%>%<-"

Once the column are created we will agroup and sum all values expend in each month.

expenses_by_month <- data %>%
  group_by(year, month) %>%
  filter(valorLíquido >= 0) %>%
  summarise(expense = sum(valorLíquido))

Error in grouped_df_impl(data, unname(vars), drop) : 
  Column `year` is unknown

Lets see the expense in a graphic.